Industrial process control and automation systems are often used to automate large and complex industrial processes, such as those in the chemical industry. These types of systems routinely include sensors, actuators, and controllers. The controllers typically receive measurements from the sensors and generate control signals for the actuators.
A distributed control system (DCS) is often implemented in conjunction with, or as part of, an industrial process control and automation system. A DCS often uses one or more Model predictive controllers (MPCs, also known as multivariable predictive controllers, or simply, multivariable controllers) in industrial processes to manage complex systems to operate at limits that are economically beneficial. Such MPCs, as well as other controllers in the DCS, may need to be configured before the controllers as implemented into a runtime DCS environment.